Indeed, that’s why I removed the discounting factors that were specific to R&D from their model (only crediting R&D with 40% of growth, and assuming only 70% diffusion of R&D to the rest of the world). Once you remove these factors, their model is a classic semi-endogenous growth model and is thus focused on the cost-effectiveness of TFP growth in the aggregate—no matter what the cause. Insofar as any path to sustained economic growth goes through productivity growth, I think their modelling framework is still very useful for evaluating the social returns to economic growth.
The only thing that is really specific to R&D is that in a semi-endogenous growth model, the number of researchers is an important input to the growth trajectory. But I am not focusing on the growth trajectory itself (which is affected by how you choose to model growth and what path is taken) - rather, I am focusing on the population welfare that arises from any given level of growth. Different paths to economic growth may yield different levels of economic growth, but they do not change the fundamental growth --> welfare mapping. So I don’t think that the focus on R&D takes away from this argument in any way.
You say things like “Once we include inequality, economic growth looks a lot less beneficial than interventions that target the extreme poor.” Insofar as I understand this sentence, you cannot conclude this unless you know about the cost of the intervention to increase economic growth. Your argument implies that the benefits of growth are lower than some models suggest, but since we don’t know anything about costs, you cannot conclude anything about cost-effectiveness. So, it’s not possible for you to conclude anything about the relative cost-effectiveness of different approaches
It’s fair to say that I’m not rigorously comparing these two approaches. What I am doing is showing that one has a 90% lower value than estimated, and the other is not affected. In general, this would lead you to update in favor of targeted interventions—hence saying that it looks better. The strength of that update may not be enough to overcome your prior. But I’m not litigating the entire growth vs RD debate here. The argument is just “inequality is a big problem for growth”.
For what it’s worth the Open Phil framework (with R&D discount factors removed) is looking at the effect of global growth, not growth in rich countries. That should attenuate the gap between their results and the results of modelling this just in LMICs. And I don’t know how big a big difference is, but to take it from my final estimate of 12X to 1000X would require growth promotion in LMICs to be over 80 times more cost effective than global growth promotion, which seems like a lot.
Indeed, that’s why I removed the discounting factors that were specific to R&D from their model (only crediting R&D with 40% of growth, and assuming only 70% diffusion of R&D to the rest of the world). Once you remove these factors, their model is a classic semi-endogenous growth model and is thus focused on the cost-effectiveness of TFP growth in the aggregate—no matter what the cause. Insofar as any path to sustained economic growth goes through productivity growth, I think their modelling framework is still very useful for evaluating the social returns to economic growth.
The only thing that is really specific to R&D is that in a semi-endogenous growth model, the number of researchers is an important input to the growth trajectory. But I am not focusing on the growth trajectory itself (which is affected by how you choose to model growth and what path is taken) - rather, I am focusing on the population welfare that arises from any given level of growth. Different paths to economic growth may yield different levels of economic growth, but they do not change the fundamental growth --> welfare mapping. So I don’t think that the focus on R&D takes away from this argument in any way.
You say things like “Once we include inequality, economic growth looks a lot less beneficial than interventions that target the extreme poor.” Insofar as I understand this sentence, you cannot conclude this unless you know about the cost of the intervention to increase economic growth. Your argument implies that the benefits of growth are lower than some models suggest, but since we don’t know anything about costs, you cannot conclude anything about cost-effectiveness. So, it’s not possible for you to conclude anything about the relative cost-effectiveness of different approaches
It’s fair to say that I’m not rigorously comparing these two approaches. What I am doing is showing that one has a 90% lower value than estimated, and the other is not affected. In general, this would lead you to update in favor of targeted interventions—hence saying that it looks better. The strength of that update may not be enough to overcome your prior. But I’m not litigating the entire growth vs RD debate here. The argument is just “inequality is a big problem for growth”.
Agreed. I would like to see this done for LMICs and not rich countries as it seems that could make a big difference.
For what it’s worth the Open Phil framework (with R&D discount factors removed) is looking at the effect of global growth, not growth in rich countries. That should attenuate the gap between their results and the results of modelling this just in LMICs. And I don’t know how big a big difference is, but to take it from my final estimate of 12X to 1000X would require growth promotion in LMICs to be over 80 times more cost effective than global growth promotion, which seems like a lot.
Yes and to be clear, I think the analysis is well done and think this adds to the debate, so I appreciate you doing this